Power AI workloads with AMD Instinct™ GPUs. Scale models faster with high-performance, dedicated cloud compute.
About the role
At TensorWave the cluster is the network: thousands of GPUs only train as one machine if the fabric between them is built and validated correctly. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- This internship is open to three kinds of candidates. We evaluate all three against the same bar and none is a second-tier track
- CCNA, JNCIA, Network+, or equivalent
- BGP or EVPN lab experience, exposure to Arista EOS, SONiC, or other data center NOS
- Git, Ansible, or NetBox experience
- HPC or GPU cluster exposure, familiarity with RDMA or RoCE concepts
More about this role
Our mission is simple: deliver seamless, secure, reliable, and resilient AI compute at scale. We've built a versatile cloud platform that eliminates infrastructure barriers, empowering builders to focus on innovation instead of fighting their stack. Because breakthrough AI should move at the speed of ideas, not infrastructure.
At TensorWave the cluster is the network: thousands of GPUs only train as one machine if the fabric between them is built and validated correctly.
We’re looking for a Network Engineering Intern to join our team during an exciting phase of growth. In this role, you will work with the engineers who bring those fabrics up, verifying cabling and links during real cluster deployments and writing the Python tooling that makes the next deployment faster and less error-prone. You will leave with code merged into the team’s repository and used on a live cluster.
This internship is open to three kinds of candidates. We evaluate all three against the same bar and none is a second-tier track.
Computer science, computer engineering, electrical engineering, IT, or network engineering programs. Homelabs, CTF teams, and open-source contributions count.
Communications,...
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